The business benefits of generative AI are significant, from boosting productivity and security to fostering innovation. However, there are also several challenges.

A recent study from the IBM Institute for Business Value reveals that 55 percent of Australian CEOs believe competitive advantage will hinge on who possesses the most advanced generative AI capabilities.

Leaders recognize the imperative to implement and scale generative AI across their organizations, but factors like employee engagement, technology integration, partnerships and productivity concerns can introduce delays.

Here are six critical realities leaders must address to stay ahead:

1. No matter how good a team is today, they may not be good enough to compete tomorrow

As generative AI evolves, businesses face a significant shift in workforce needs, cultural mindsets, governance frameworks and innovation strategies.

CEOs recognize this challenge, saying their organization must take advantage of technologies that are changing faster than employees can adapt – and that they’re pushing their organization to adopt generative AI more quickly than some people are comfortable with.

Adding to the uncertainty is the need to plan for it. Especially when it comes to their employees. More than half of respondents (60%) have yet to assess the impact of generative AI on their employees.

An estimated 35 percent of the workforce will require retraining and reskilling over the next three years – a daunting task, considering the pace of change in generative AI.

As we approach the second anniversary of ChatGPT’s release, we’ve witnessed the growth of many new generative AI capabilities from Google, Anthropic, IBM, Mistral AI, NVIDIA, xAI, Meta, Perplexity and others, in addition to OpenAI, which released ChatGPT on 30 November 2022. Keeping up with this pace is extremely challenging.

Employees involved in implementing generative AI solutions need to stay abreast of an evolving array of techniques, such as integrating AI with existing data, utilizing planning and reasoning in AI, creating system agents for complex workflows, and addressing technical needs for performance, safety, explainability and cost-effectiveness.

In Australia, 53 percent of CEOs are hiring for generative AI roles that did not exist last year, while 47 percent expect to reduce or redeploy their workforce in the next 12 months because of generative AI. Employees who leverage AI will replace those who do not.

2. Customers don’t know what they’ll want in the future

Generative AI can help companies tap into stores of customer data – from in-depth market research to individual device metrics – to develop innovative product ideas.

Language-based AI has extended into many other modalities that generate images, videos, code, sounds and even fully formed podcasts and multistep computer tasks from a simple prompt.

These advancements are introducing an unprecedented collection of accessible tools for creative endeavors.

The general perception of what is technically possible, accessible, affordable and easy is being challenged daily as new generative AI tools are released. Waiting to hear what the customer wants is likely to let more innovative and bolder competitors whiz past to the front of the line.

Until recently, hyper-personalization at scale seemed like a dream. Generative AI has changed the game by helping us recognize complex patterns quickly and build scalable solutions.

The reality is that these tools have democratized intelligence and are available to practically anyone, anywhere in the world.

Customer opinion may not always be reliable when it comes to introducing disruption and challenging existing norms in the pursuit of innovation.

3. CEOs need to trust the partners they bring to the table

Generative AI’s impact on every aspect of business will be undeniably transformative. The development of many tools is not only advancing in sophistication but also in versatility, requiring new expertise to integrate effectively into enterprises.

Partners investing in the essential expertise and evolving alongside these technologies are increasingly sought after, overshadowing those who remain complacent.

While positive sentiments and shared values are crucial to successful partnerships, CEOs must avoid the temptation to cling to familiarity. The necessity to prioritize new, strategically beneficial partnerships over some long-standing relationships is becoming apparent.

As generative AI’s impact reaches deeper into the value chain, CEOs will need to loosen control over certain areas of their business to focus on what truly matters.

Establishing trust with new and renewed partners and being comfortable relying on their expertise will be essential for managing areas most affected by emerging synthetic intelligence tools.

Prioritizing connections over capabilities could be a significant risk, especially as businesses strive for a competitive edge through generative AI.

4. The C-suite shouldn’t always agree

Diversity in perspectives is a key advantage in these uncertain times. Fostering empathetic debate and constructive collaboration can bring to light issues that might otherwise remain hidden in a habitually compliant environment.

Determining the way forward is becoming increasingly challenging as established norms are upended. Generative AI is challenging the cognitive and reasoning skills that humans once considered the final frontier of intelligence. These changes are proliferating not only within enterprises but also in our homes and personal spaces.

No single authority can confidently predict the trajectory of what some refer to as the ‘intelligence explosion.’ Diversity of perspectives is crucial for making difficult decisions – deciding what steps to take now, what to defer until more clarity emerges and what to avoid altogether.

In this evolving landscape, leaders must embrace differing viewpoints and encourage open discussions that go beyond mere consensus. By cultivating an environment where diverse perspectives are respected and rigorously examined, the C-suite can make more balanced, resilient decisions that are better equipped to handle the complexity and unfolding uncertainty.

5. Generative AI will continue to make people uncomfortable

Exponential growth remains a challenging concept for the human brain to grasp. The realization of the scale of change often comes too late, leaving us with limited or no control, leading many to resist change and, by extension, progress.

In areas such as language, mathematics, art and increasingly complex planning, generative AI is developing superhuman capabilities, already surpassing average human performance by a significant margin. For organizations, harnessing these technologies is essential to remain competitive.

At the same time, 61 percent of global CEOs are considering the adoption of generative AI, which will undoubtedly make some employees uneasy. To gain buy-in, companies need to invest in training to help employees understand how these tools can enhance their jobs, making them easier, more productive and more fulfilling.

Balancing technical and change management considerations are essential. Implementing training, governance, guardrails and policies early can increase confidence in generative AI and foster a safer environment for its adoption.

6. CEOs know that tech shortcuts hinder progress

Nearly half (49%) of Australian CEOs state that piloting and experimentation were the primary objectives of their investments in generative AI. The majority of these experiments focus on productivity and efficiency outcomes.

CEOs expect AI to be the leading driver of cost savings within the next two years and are reallocating resources from long-term to short-term initiatives. However, they also acknowledge that this emphasis on short-term gains is their number one barrier to innovation.

While tech shortcuts help demonstrate proof of concept, they are a far cry from the complexities of implementing these solutions at scale. The technical, practical and economic considerations for scaling generative AI are more challenging than the initial, clever applications of a large language model to produce an elegant result from a subset of business data.

For these experiments to not become dead ends, each must include considerations for enterprise-wide adoption and a solid business case for full implementation. Without this foresight, isolated pilot programs risk stalling rather than driving meaningful transformation.

Ultimately, if businesses are to harness the full potential of generative AI, they must move beyond quick wins and commit to building scalable, resilient AI solutions that are embedded in their long-term strategic vision.